A study of variability of annual river flow of the southern African region

Abstract

Variability of river flow is investigated in 502 river flow gauging stations in nine countries of the southern African region with a view to document the spatial variability of the river flow regimes. Those regions where there is strong evidence of declining or increasing trend in annual runoff have been identified. The study has shown that runoff in the region ranges from over 320 mm year^?1 in the Lower Zambezi and the highlands of Tanzania to less than 10 mm year^?1 in the deserts of Namibia and the Kalahari. There is also evidence of declining runoff in parts of Zambia, Angola, Mozambique and the High Veld in South Africa. The recent decline seems to have started from around 1975.     

Extreme events as drivers of early human behaviour in Africa? The case for variability,not catastrophic drought

Extreme Late Quaternary climatic events, sometimes of considerable continental extent, are being proposed as major contributors to ancestral human behaviour, particularly migration, in Africa. Most recently, a catastrophic drought in the Afro‐Asian monsoon region has been proposed for 16 000–17 000 years ago, driven by global impacts of the Heinrich event 1 (H1), with potentially significant consequences for Palaeolithic cultures. We provide a new analysis of the assertion and find, on examination of a wide set of palaeoenvironmental records, that the scale and extent of the proposed drought is not supported. While some parts of the African tropics, close to the equator, do appear dry at this time, data for the tropics as a whole suggest markedly variable terrestrial conditions, with some environmental systems experiencing very positive hydrological excursions during H1. We contend that in the quest for evidence of climate drivers of ancestral human behaviour, the variability associated with spatially and temporally complex climatic conditions is a significant factor in itself. Copyright © 2011 John Wiley & Sons, Ltd.     

Relations indices de Végétation–Pluie au Burkina Faso: Cas du Bassin Versant du Nakambé/Relationship between Rainfall and Vegetation Indexes in Burkina Faso: A Case Study of the Nakambé Basin

Abstract

This work deals with the problem of the use of remote sensing data derived from NOAA/AVHRR observations for monitoring the West African Sahel climatic variability. NDVI is widely used in hydrological and climatological research, and in the study of global climatic changes. The relationships between NDVI and climatic parameters are not well established yet and are the focus of many studies. The relationships between NDVI and rainfall were studied at a 10-day time step in the Nakambe River basin in Burkina Faso in the Sahelo-Sudanian area over the years 1982–1999. Good correlations were found in the annual evolution of these two variables. The statistical analysis shows a significant relationship between NDVI and the sum of the annual rainfall with determination coefficients greater than 0.80. At the spatial scale of 0.5° × 0.5°, the determination coefficient ranges from 0.91 to 0.96. It was also found that the NDVI is a good indicator of the determination of the beginning and the end of the rainy season. It gives reasonably good results in comparison with the other methods commonly used in the study region.     

Spatial–temporal variability and hydrologic connectivity of runoff generation areas in a North Alabama pasture—implications for phosphorus transport

This study delineated spatially and temporally variable runoff generation areas in the Sand Mountain region pasture of North Alabama under natural rainfall conditions, and demonstrated that hydrologic connectivity is important for generating hillslope response when infiltration‐excess (IE) runoff mechanism dominates. Data from six rainfall events (13·7–32·3 mm) on an intensively instrumented pasture hillslope (0·12 ha) were analysed. Analysis of data from surface runoff sensors, tipping bucket rain gauge and HS‐flume demonstrated spatial and temporal variability in runoff generation areas. Results showed that the maximum runoff generation area, which contributed to runoff at the outlet of the hillslope, varied between 67 and 100%. Furthermore, because IE was the main runoff generation mechanism on the hillslope, the data showed that as the rainfall intensity changed during a rainfall event, the runoff generation areas expanded or contracted. During rainfall events with high‐intensity short‐ to medium‐duration, 4–8% of total rainfall was converted to runoff at the outlet. Rainfall events with medium‐ to low‐intensity, medium‐duration were found less likely to generate runoff at the outlet. In situ soil hydraulic conductivity (k) was measured across the hillslope, which confirmed its effect on hydrologic connectivity of runoff generation areas. Combined surface runoff sensor and k‐interpolated data clearly showed that during a rainfall event, lower k areas generate runoff first, and then, depending on rainfall intensity, runoff at the outlet is generated by hydrologically connected areas. It was concluded that in IE‐runoff‐dominated areas, rainfall intensity and k can explain hydrologic response. The study demonstrated that only connected areas of low k values generate surface runoff during high‐intensity rainfall events. Identification of these areas would serve as an important foundation for controlling nonpoint source pollutant transport, especially phosphorus. The best management practices can be developed and implemented to reduce transport of phosphorus from these hydrologically connected areas. Copyright © 2009 John Wiley & Sons, Ltd.     

Accounting for sparsely observed rainfall space—time variability in a rainfall—runoff model of a semiarid Tunisian basin/Prise en compte d'observations peu denses de la variabilité spatiotemporelle de la pluie dans une modélisation pluie—débit d'un bassin semi-aride Tunisien

Abstract

The management of water excesses and deficits is a major task in semiarid Mediterranean regions, where the variability of rainfall inputs is high at different time and space scales. Thus intense hydrometeorological events, which generate both potential resource and hazards, are of major interest. A simple method is proposed, with the example of the Skhira basin (192 km²) in central Tunisia, to account for the event space–time variability of rainfall in a rainfall–runoff model, in order to check its influence on the shape, magnitude and timing of resulting hydrographs. The transfer function used is a geomorphology-based unit hydrograph with an explicit territorial significance. Simulations made for highly variable events show the relevance of this method, seen as the first step of a downward approach, and its robustness with respect to the quality and the density of rainfall data.     

Daily variability of river concentrations and fluxes: indicators based on the segmentation of the rating curve

The variability of water chemistry on a daily scale is rarely addressed due to the lack of records. Appropriate tools, such as typologies and dimensionless indicators, which permit comparisons between stations and between river materials, are missing. Such tools are developed here for daily concentrations (C), specific fluxes or yields (Y) and specific river flow (q). The data set includes 128 long‐term daily records, for suspended particulate matter (SPM), total dissolved solids (TDS), dissolved and total nutrients, totalling 1236 years of records. These 86 river basins (10³–10⁶ km²) cover a wide range of environmental conditions in semi‐arid and temperate regions. The segmentation—truncation of C–q rating curves into two parts at median flows (q₅₀) generates two exponents (b_50inf and b_50sup) that are different for 66% of the analysed rating curves. After segmentation, the analysis of records results in the definition of nine major C–q types combining concentrating, diluting or stable patterns, showing inflexions, chevron and U shapes. SPM and TDS are preferentially distributed among a few types, while dissolved and total nutrients are more widely distributed. Four dimensionless indicators of daily variability combine median (C₅₀, Y₅₀), extreme (C₉₉, Y₉₉) and flow‐weighted (C*, Y*) concentrations and yields (e.g. C₉₉/C₅₀, Y*/Y₅₀). They vary over two to four orders of magnitude in the analysed records, discriminating stations and river material. A second set of four indicators of relative variability [e.g. (Y*/Y₅₀)/(q*/q₅₀)], takes into account the daily flow variability, as expressed by q*/q₅₀ and q₉₉/q₅₀, which also vary over multiple orders of magnitude. The truncated exponent b_50sup is used to describe fluxes at higher flows accounting for 75% (TDS) to 97% (SPM) of interannual fluxes. It ranges from ? 0·61 to + 1·86 in the database. It can be regarded as the key amplificator (positive b_50sup) or reductor (negative b_50sup) of concentrations or yields variability. C₅₀, Y₅₀, b_50sup can also be estimated in discrete surveys, which provides a new perspective for quantifying and mapping water quality variability at daily scale. Copyright © 2011 John Wiley & Sons, Ltd.     

A 200-year precipitation index for the central English Lake District / Un indice de précipitation de 200 ans pour la Région des Lacs en Angleterre

Abstract

Abstract The geographical context and hydroclimatology of the English Lake District means that the region is an important monitor of changes to nationally significant environmental assets. Using monthly rainfall series for sites in and around the central Lake District, a continuous ~200-year precipitation index was constructed for a representative station close to Grasmere. The bridged series shows a significant decline in summer rainfall since the 1960s, offset by increases in winter and spring that are strongly linked to North Atlantic forcing. Over longer time periods, the index exhibits several notable dry (1850s, 1880s, 1890s, 1930s, 1970s) and wet (1820s, 1870s, 1920s, 1940s, 1990s) decades. These patterns are strongly reflected by reservoir inflow series and by indicators of the biological status of the region’s freshwater lakes. It is argued that long-term climate indices will become increasingly important as managers seek to evaluate recent and project environmental changes within the context of long-term natural variability.     

Generation of correlated properties in heterogeneous porous media

The spatial distribution of rock properties in porous media, such as permeability and porosity, often is strongly variable. Therefore, these properties usefully may be considered as a random field. However, this variability is correlated frequently on length scales comparable to geological lengths (for example, scales of sand bodies or facies). To solve various engineering problems (for example, in the oil recovery process) numerical models of a porous medium often are used. A need exists then to understand correlated random fields and to generate them over discretized numerical grids. The paper describes the general mathematical methods required to do this, with one particular method (the nearest neighbor model) described in detail. How parameters of the mathematical model may be related to rock property statistics for the nearest neighbor model is shown. The method is described in detail in one, two, and three dimensions. Examples are given of how model parameters may be determined from real data.     

Modeling long term lake variations by physically based stochastic dynamic models

Several physically based stochastic dynamic models (SDM) are described including year-to-year variations of water volume in terminal and non-terminal lakes, streamflow of lake-fed rivers, and salinity of an inland sea (the Sea of Azov). All of these models are based upon the SDM of water volume of terminal lakes developed by Kritzky and Menkel in 1946 in co-operation with Kolomogorov. Explicit formulae are derived for second order statistical moments of the output processes, including variance, correlation function, spectra, etc., under the assumption that the forcing functions from stationary random sequences. The least-squares prediction problem is solved for both stationary and non-stationary cases. Some of the processes are shown to possess high statistical predictability. Actual predictions are compared with independent observations. Problems for further study are stated.